Increasing Fusarium Head Blight Resistance Breeding Resources in Bread Wheat
Bibliographic record
Abstract
Fusarium head blight (FHB), caused by Fusarium spp., is a destructive disease of cereal crops globally. It causes decreased yield, loss of quality, and potential mycotoxin contamination of harvested grain. Integrated pest management (IPM) strategies are required to mitigate the effects of FHB; using cultural control methods, appropriate fungicide application, and planting varieties with moderate or higher resistance ratings are used in combination. Planting a variety with elevated resistance is a vital component to IPM; however, there are limited resistant varieties available to producers. Breeding for FHB resistance is complicated, and sources of resistance are few. A continual search is ongoing for novel sources of resistance and other resources to aid in breeding efforts. The objective of this thesis is to aid in this search for novel sources of resistance and additional resources. Within this thesis, 11 minor and one major quantitative trait loci were identified in a RIL population with Agropyron repens L. ancestry; a wild relative to wheat identified as a possible source of FHB resistance. A detached leaf assay was also investigated in the hopes of saving time and resources in FHB resistance breeding. One moderately, inverse correlation was identified between incubation time and deoxynivalenol content in barley. Additionally, a phenotypic evaluation and preliminary Genome Wide Association Study was performed on Plant Gene Resources of Canada accessions. Four accessions were identified to have elevated FHB resistance based on best linear unbiased predictors. Thirteen SNPs were also associated with resistance within the population. The results of this thesis will aid wheat breeders in their efforts to breed for FHB resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".